qiaoqichaoandClaude Code
d56c699ce6
按 docs/v2/05-implementation-plan.md §1 候选迁移表与 claude_use/T00 白名单， 从 55e2cdb 抽取 224 个文件（2.48 MB）到独立目录 F:/mini-OpenClaw-v2。 - 排除：凭据(.env/server-deploy.conf/旧DELIVERY.md)、运行数据(xingbang_data 等 4 个 SQLite)、依赖(venv/node_modules 符号链接)、归档(_backup*/test-evidence/ ori_file)、Office 临时文件 - 目标目录独立 git 仓库，初始恢复点；Gitea 远程与分支待 OQ-06 Q2 定案 - 未部署、未启动服务、未调用模型 Co-Authored-By: Claude Code <noreply@anthropic.com>
79 lines
4.6 KiB
Python
79 lines
4.6 KiB
Python
"""Same read-only query/alignment contract for mock data and approved SQL sources."""
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from copy import deepcopy
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from decimal import Decimal
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from api import risk_agent_config as catalog
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from services.assistant_store import uid, digest
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from services.assistant_materials import NUMERIC, scalar
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from services.skill_executor import number
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from api.risk_agent_alignment import MONEY_FIELDS, SCALE
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def load_catalog():
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with catalog._db() as db:
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return {kind: catalog._all(db, kind) for kind in catalog.SEED}
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def read_cards(project, components):
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values, sources = deepcopy(project["values"]), {}
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for field, refs in project["sources"].items():
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sources[field] = [r for r in refs if r["id"] == project["selected_sources"].get(field)]
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datasets, errors = [], []
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if project.get("pending_candidates"):
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errors.append({"card_id": "materials", "message": "存在尚未人工确认的材料候选，本次仍使用已确认事实"})
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samples = {}
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for (table, rows), mapping in zip(catalog.SAMPLES.items(), catalog.MAPPINGS):
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row = {key: None for key in rows[0]}
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row["project_id"] = project["id"]
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for field, column in mapping.items():
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row[column] = values.get(field)
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row.update(project_id=project["id"])
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if table == "project":
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row["customer_name"] = project["customer"]
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if table == "finance":
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row.update(period=project.get("period", "2025"), scope=project.get("scope", "合并"))
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samples[table] = [row]
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for card in components.get("legacy_cards", []):
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connection = next(c for c in components["legacy_connections"] if c["id"] == card["connection"])
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if connection.get("data_domain", "demo" if connection.get("type") == "demo" else "production") != project["data_domain"]:
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raise ValueError("演示数据与正式数据源不可混用")
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try:
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rows = catalog.query_card(card, connection, project["id"], demo_samples=samples, exact_decimals=True)
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records, selected = catalog.align(card, rows, project["id"], project.get("period", "2025"))
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datasets.append({"card_id": card["id"], "name": card["name"], "version": card["version"], "records": records, "row_hash": digest(rows)})
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if selected is None:
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errors.append({"card_id": card["id"], "message": "多期或多口径记录未选择，未合并计算"})
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continue
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for field, column in card.get("mapping", {}).items():
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raw = selected["values"].get(field)
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if field in NUMERIC:
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raw = selected["raw"].get(column)
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unit = card.get("field_units", {}).get(field, card.get("unit") if field in MONEY_FIELDS else None)
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if raw is not None and unit:
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raw = number(raw) * SCALE[unit]
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raw = scalar(field, raw)
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# Mock SQL uses the actual parsed fixture values; retain their file locators.
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if connection.get("type") == "demo" and field in sources:
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same = values.get(field) == raw
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if field in NUMERIC and values.get(field) is not None and raw is not None:
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same = number(values[field]) == number(raw)
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if not same:
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values[field] = None
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errors.append({"card_id": card["id"], "message": field + "映射结果与原始材料冲突"})
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continue
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ref = {"id": uid("ev"), "project_id": project["id"], "field": field, "value": raw,
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"source": card["name"], "locator": "数据卡字段 " + column, "card_id": card["id"], "version": card["version"],
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"period": selected["period"], "scope": selected["scope"], "unit": selected["units"].get(field), "currency": card.get("currency", "CNY")}
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same = values.get(field) == raw
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if field in NUMERIC and values.get(field) is not None and raw is not None:
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same = number(values[field]) == number(raw)
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if field in values and not same:
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values[field] = None
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errors.append({"card_id": card["id"], "message": field + "多来源冲突，请人工确认"})
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else:
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values[field] = raw
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sources.setdefault(field, []).append(ref)
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except Exception as exc:
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# No connection strings/credentials in project-facing diagnostics.
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errors.append({"card_id": card["id"], "message": "数据卡读取或口径校验失败", "error_type": type(exc).__name__})
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return values, sources, datasets, errors
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